Overview

Dataset statistics

Number of variables26
Number of observations29601
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 MiB
Average record size in memory201.0 B

Variable types

Numeric22
Categorical3
Boolean1

Warnings

PayStat/Sept05 is highly correlated with PayStat/Aug05 and 4 other fieldsHigh correlation
PayStat/Aug05 is highly correlated with PayStat/Sept05 and 5 other fieldsHigh correlation
PayStat/Jul05 is highly correlated with PayStat/Sept05 and 5 other fieldsHigh correlation
PayStat/Jun05 is highly correlated with PayStat/Sept05 and 5 other fieldsHigh correlation
PayStat/May05 is highly correlated with PayStat/Sept05 and 5 other fieldsHigh correlation
PayStat/Apr05 is highly correlated with PayStat/Aug05 and 4 other fieldsHigh correlation
Outstanding/Sept05 is highly correlated with Outstanding/Aug05 and 4 other fieldsHigh correlation
Outstanding/Aug05 is highly correlated with Outstanding/Sept05 and 4 other fieldsHigh correlation
Outstanding/Jul05 is highly correlated with Outstanding/Sept05 and 4 other fieldsHigh correlation
Outstanding/Jun05 is highly correlated with Outstanding/Sept05 and 4 other fieldsHigh correlation
Outstanding/May05 is highly correlated with Outstanding/Sept05 and 4 other fieldsHigh correlation
Outstanding/Apr05 is highly correlated with Outstanding/Sept05 and 4 other fieldsHigh correlation
PayStats is highly correlated with PayStat/Sept05 and 5 other fieldsHigh correlation
PayStat/Sept05 is highly correlated with PayStat/Aug05 and 3 other fieldsHigh correlation
PayStat/Aug05 is highly correlated with PayStat/Sept05 and 8 other fieldsHigh correlation
PayStat/Jul05 is highly correlated with PayStat/Sept05 and 10 other fieldsHigh correlation
PayStat/Jun05 is highly correlated with PayStat/Sept05 and 11 other fieldsHigh correlation
PayStat/May05 is highly correlated with PayStat/Aug05 and 9 other fieldsHigh correlation
PayStat/Apr05 is highly correlated with PayStat/Aug05 and 9 other fieldsHigh correlation
Outstanding/Sept05 is highly correlated with PayStat/Aug05 and 9 other fieldsHigh correlation
Outstanding/Aug05 is highly correlated with PayStat/Aug05 and 11 other fieldsHigh correlation
Outstanding/Jul05 is highly correlated with PayStat/Aug05 and 12 other fieldsHigh correlation
Outstanding/Jun05 is highly correlated with PayStat/Jul05 and 14 other fieldsHigh correlation
Outstanding/May05 is highly correlated with PayStat/Jul05 and 14 other fieldsHigh correlation
Outstanding/Apr05 is highly correlated with PayStat/Jun05 and 12 other fieldsHigh correlation
Paid/Sept05 is highly correlated with Outstanding/Sept05 and 5 other fieldsHigh correlation
Paid/Aug05 is highly correlated with Outstanding/Jul05 and 5 other fieldsHigh correlation
Paid/Jul05 is highly correlated with Outstanding/Jun05 and 7 other fieldsHigh correlation
Paid/Jun05 is highly correlated with Outstanding/Jun05 and 6 other fieldsHigh correlation
Paid/May05 is highly correlated with Outstanding/Jun05 and 5 other fieldsHigh correlation
Paid/Apr05 is highly correlated with Outstanding/May05 and 4 other fieldsHigh correlation
PayStats is highly correlated with PayStat/Sept05 and 11 other fieldsHigh correlation
Unnamed: 0 is highly correlated with DefaultHigh correlation
Credit Limit is highly correlated with PayStat/Aug05 and 5 other fieldsHigh correlation
Age is highly correlated with DefaultHigh correlation
PayStat/Sept05 is highly correlated with DefaultHigh correlation
PayStat/Aug05 is highly correlated with Credit Limit and 1 other fieldsHigh correlation
PayStat/Jul05 is highly correlated with Credit Limit and 1 other fieldsHigh correlation
PayStat/Jun05 is highly correlated with Credit Limit and 1 other fieldsHigh correlation
PayStat/May05 is highly correlated with Credit Limit and 1 other fieldsHigh correlation
PayStat/Apr05 is highly correlated with Credit Limit and 1 other fieldsHigh correlation
Outstanding/Sept05 is highly correlated with Outstanding/Aug05 and 5 other fieldsHigh correlation
Outstanding/Aug05 is highly correlated with Outstanding/Sept05 and 5 other fieldsHigh correlation
Outstanding/Jul05 is highly correlated with Outstanding/Sept05 and 5 other fieldsHigh correlation
Outstanding/Jun05 is highly correlated with Outstanding/Sept05 and 5 other fieldsHigh correlation
Outstanding/May05 is highly correlated with Outstanding/Sept05 and 5 other fieldsHigh correlation
Outstanding/Apr05 is highly correlated with Outstanding/Sept05 and 5 other fieldsHigh correlation
Paid/Sept05 is highly correlated with DefaultHigh correlation
Paid/Aug05 is highly correlated with DefaultHigh correlation
Paid/Jul05 is highly correlated with DefaultHigh correlation
Paid/Jun05 is highly correlated with DefaultHigh correlation
Paid/May05 is highly correlated with DefaultHigh correlation
Paid/Apr05 is highly correlated with DefaultHigh correlation
Default is highly correlated with Unnamed: 0 and 20 other fieldsHigh correlation
Marital Status is highly correlated with AgeHigh correlation
Credit Limit is highly correlated with Outstanding/Aug05 and 5 other fieldsHigh correlation
Outstanding/Aug05 is highly correlated with Credit Limit and 6 other fieldsHigh correlation
Paid/May05 is highly correlated with Paid/Aug05 and 1 other fieldsHigh correlation
PayStat/Jun05 is highly correlated with PayStat/May05 and 5 other fieldsHigh correlation
PayStat/May05 is highly correlated with PayStat/Jun05 and 6 other fieldsHigh correlation
Outstanding/Jun05 is highly correlated with Credit Limit and 6 other fieldsHigh correlation
Outstanding/May05 is highly correlated with Credit Limit and 8 other fieldsHigh correlation
Paid/Sept05 is highly correlated with Paid/Aug05 and 2 other fieldsHigh correlation
Paid/Aug05 is highly correlated with Paid/May05 and 3 other fieldsHigh correlation
PayStat/Jul05 is highly correlated with PayStat/Jun05 and 5 other fieldsHigh correlation
Paid/Jun05 is highly correlated with Paid/Sept05 and 1 other fieldsHigh correlation
PayStat/Apr05 is highly correlated with PayStat/Jun05 and 6 other fieldsHigh correlation
Age is highly correlated with Marital StatusHigh correlation
PayStats is highly correlated with PayStat/Jun05 and 5 other fieldsHigh correlation
PayStat/Aug05 is highly correlated with PayStat/Jun05 and 5 other fieldsHigh correlation
Default is highly correlated with PayStat/Sept05High correlation
PayStat/Sept05 is highly correlated with PayStat/Jun05 and 6 other fieldsHigh correlation
Outstanding/Sept05 is highly correlated with Credit Limit and 6 other fieldsHigh correlation
Outstanding/Apr05 is highly correlated with Credit Limit and 6 other fieldsHigh correlation
Outstanding/Jul05 is highly correlated with Outstanding/Aug05 and 6 other fieldsHigh correlation
Paid/Jul05 is highly correlated with Credit Limit and 8 other fieldsHigh correlation
Paid/Aug05 is highly skewed (γ1 = 30.62926199) Skewed
Unnamed: 0 is uniformly distributed Uniform
Unnamed: 0 has unique values Unique
PayStat/Sept05 has 14499 (49.0%) zeros Zeros
PayStat/Aug05 has 15476 (52.3%) zeros Zeros
PayStat/Jul05 has 15518 (52.4%) zeros Zeros
PayStat/Jun05 has 16204 (54.7%) zeros Zeros
PayStat/May05 has 16684 (56.4%) zeros Zeros
PayStat/Apr05 has 16053 (54.2%) zeros Zeros
Outstanding/Sept05 has 1981 (6.7%) zeros Zeros
Outstanding/Aug05 has 2466 (8.3%) zeros Zeros
Outstanding/Jul05 has 2826 (9.5%) zeros Zeros
Outstanding/Jun05 has 3143 (10.6%) zeros Zeros
Outstanding/May05 has 3433 (11.6%) zeros Zeros
Outstanding/Apr05 has 3929 (13.3%) zeros Zeros
Paid/Sept05 has 5192 (17.5%) zeros Zeros
Paid/Aug05 has 5334 (18.0%) zeros Zeros
Paid/Jul05 has 5891 (19.9%) zeros Zeros
Paid/Jun05 has 6318 (21.3%) zeros Zeros
Paid/May05 has 6600 (22.3%) zeros Zeros
Paid/Apr05 has 7043 (23.8%) zeros Zeros
PayStats has 2470 (8.3%) zeros Zeros

Reproduction

Analysis started2021-07-30 01:01:00.299140
Analysis finished2021-07-30 01:05:32.403759
Duration4 minutes and 32.1 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ≥0)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct29601
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14971.75893
Minimum1
Maximum30000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:32.524397image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1495
Q17474
median14953
Q322463
95-th percentile28488
Maximum30000
Range29999
Interquartile range (IQR)14989

Descriptive statistics

Standard deviation8660.18443
Coefficient of variation (CV)0.5784346697
Kurtosis-1.199491067
Mean14971.75893
Median Absolute Deviation (MAD)7494
Skewness0.004481755181
Sum443179036
Variance74998794.35
MonotonicityStrictly increasing
2021-07-29T19:05:32.676989image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
< 0.1%
199651
 
< 0.1%
199631
 
< 0.1%
199621
 
< 0.1%
199611
 
< 0.1%
199601
 
< 0.1%
199591
 
< 0.1%
199581
 
< 0.1%
199571
 
< 0.1%
199561
 
< 0.1%
Other values (29591)29591
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
300001
< 0.1%
299991
< 0.1%
299981
< 0.1%
299971
< 0.1%
299961
< 0.1%
299951
< 0.1%
299941
< 0.1%
299931
< 0.1%
299921
< 0.1%
299911
< 0.1%

Credit Limit
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct81
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167550.5449
Minimum10000
Maximum1000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:32.842587image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile20000
Q150000
median140000
Q3240000
95-th percentile430000
Maximum1000000
Range990000
Interquartile range (IQR)190000

Descriptive statistics

Standard deviation129944.021
Coefficient of variation (CV)0.7755511689
Kurtosis0.5318491585
Mean167550.5449
Median Absolute Deviation (MAD)90000
Skewness0.9928498687
Sum4959663680
Variance1.688544858 × 1010
MonotonicityNot monotonic
2021-07-29T19:05:33.012176image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500003331
 
11.3%
200001955
 
6.6%
300001586
 
5.4%
800001542
 
5.2%
2000001498
 
5.1%
1500001080
 
3.6%
1000001035
 
3.5%
180000979
 
3.3%
360000872
 
2.9%
60000819
 
2.8%
Other values (71)14904
50.3%
ValueCountFrequency (%)
10000486
 
1.6%
160001
 
< 0.1%
200001955
6.6%
300001586
5.4%
40000226
 
0.8%
500003331
11.3%
60000819
 
2.8%
70000726
 
2.5%
800001542
5.2%
90000641
 
2.2%
ValueCountFrequency (%)
10000001
 
< 0.1%
8000002
 
< 0.1%
7800002
 
< 0.1%
7600001
 
< 0.1%
7500004
< 0.1%
7400002
 
< 0.1%
7300002
 
< 0.1%
7200003
 
< 0.1%
7100006
< 0.1%
7000008
< 0.1%

Sex
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size231.4 KiB
F
17855 
M
11746 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters29601
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF
2nd rowF
3rd rowF
4th rowF
5th rowM

Common Values

ValueCountFrequency (%)
F17855
60.3%
M11746
39.7%

Length

2021-07-29T19:05:33.270110image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-07-29T19:05:33.342961image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
ValueCountFrequency (%)
f17855
60.3%
m11746
39.7%

Most occurring characters

ValueCountFrequency (%)
F17855
60.3%
M11746
39.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter29601
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F17855
60.3%
M11746
39.7%

Most occurring scripts

ValueCountFrequency (%)
Latin29601
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
F17855
60.3%
M11746
39.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII29601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F17855
60.3%
M11746
39.7%

Education
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size231.4 KiB
BSc
14024 
MSc or PHd
10581 
High School Diploma
4873 
Other
 
123

Length

Max length19
Median length10
Mean length8.144454579
Min length3

Characters and Unicode

Total characters241084
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBSc
2nd rowBSc
3rd rowBSc
4th rowBSc
5th rowBSc

Common Values

ValueCountFrequency (%)
BSc14024
47.4%
MSc or PHd10581
35.7%
High School Diploma4873
 
16.5%
Other123
 
0.4%

Length

2021-07-29T19:05:33.573854image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-07-29T19:05:33.660582image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
ValueCountFrequency (%)
bsc14024
23.2%
msc10581
17.5%
or10581
17.5%
phd10581
17.5%
high4873
 
8.1%
school4873
 
8.1%
diploma4873
 
8.1%
other123
 
0.2%

Most occurring characters

ValueCountFrequency (%)
30908
12.8%
S29478
12.2%
c29478
12.2%
o25200
10.5%
H15454
 
6.4%
B14024
 
5.8%
r10704
 
4.4%
M10581
 
4.4%
P10581
 
4.4%
d10581
 
4.4%
Other values (11)54095
22.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125062
51.9%
Uppercase Letter85114
35.3%
Space Separator30908
 
12.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c29478
23.6%
o25200
20.2%
r10704
 
8.6%
d10581
 
8.5%
h9869
 
7.9%
i9746
 
7.8%
l9746
 
7.8%
g4873
 
3.9%
p4873
 
3.9%
m4873
 
3.9%
Other values (3)5119
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
S29478
34.6%
H15454
18.2%
B14024
16.5%
M10581
 
12.4%
P10581
 
12.4%
D4873
 
5.7%
O123
 
0.1%
Space Separator
ValueCountFrequency (%)
30908
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin210176
87.2%
Common30908
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
S29478
14.0%
c29478
14.0%
o25200
12.0%
H15454
 
7.4%
B14024
 
6.7%
r10704
 
5.1%
M10581
 
5.0%
P10581
 
5.0%
d10581
 
5.0%
h9869
 
4.7%
Other values (10)44226
21.0%
Common
ValueCountFrequency (%)
30908
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII241084
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30908
12.8%
S29478
12.2%
c29478
12.2%
o25200
10.5%
H15454
 
6.4%
B14024
 
5.8%
r10704
 
4.4%
M10581
 
4.4%
P10581
 
4.4%
d10581
 
4.4%
Other values (11)54095
22.4%

Marital Status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size231.4 KiB
Single
15806 
Married
13477 
Other
 
318

Length

Max length7
Median length6
Mean length6.444545792
Min length5

Characters and Unicode

Total characters190765
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMarried
2nd rowSingle
3rd rowSingle
4th rowMarried
5th rowMarried

Common Values

ValueCountFrequency (%)
Single15806
53.4%
Married13477
45.5%
Other318
 
1.1%

Length

2021-07-29T19:05:33.909943image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-07-29T19:05:34.000715image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
ValueCountFrequency (%)
single15806
53.4%
married13477
45.5%
other318
 
1.1%

Most occurring characters

ValueCountFrequency (%)
e29601
15.5%
i29283
15.4%
r27272
14.3%
S15806
8.3%
n15806
8.3%
g15806
8.3%
l15806
8.3%
M13477
7.1%
a13477
7.1%
d13477
7.1%
Other values (3)954
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter161164
84.5%
Uppercase Letter29601
 
15.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e29601
18.4%
i29283
18.2%
r27272
16.9%
n15806
9.8%
g15806
9.8%
l15806
9.8%
a13477
8.4%
d13477
8.4%
t318
 
0.2%
h318
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
S15806
53.4%
M13477
45.5%
O318
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin190765
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e29601
15.5%
i29283
15.4%
r27272
14.3%
S15806
8.3%
n15806
8.3%
g15806
8.3%
l15806
8.3%
M13477
7.1%
a13477
7.1%
d13477
7.1%
Other values (3)954
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII190765
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e29601
15.5%
i29283
15.4%
r27272
14.3%
S15806
8.3%
n15806
8.3%
g15806
8.3%
l15806
8.3%
M13477
7.1%
a13477
7.1%
d13477
7.1%
Other values (3)954
 
0.5%

Age
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct56
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.46407216
Minimum21
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:34.108425image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile23
Q128
median34
Q341
95-th percentile53
Maximum79
Range58
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.213243334
Coefficient of variation (CV)0.2597909031
Kurtosis0.05551028991
Mean35.46407216
Median Absolute Deviation (MAD)6
Skewness0.7373094047
Sum1049772
Variance84.88385273
MonotonicityNot monotonic
2021-07-29T19:05:34.261976image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
291593
 
5.4%
271455
 
4.9%
281397
 
4.7%
301382
 
4.7%
261245
 
4.2%
311205
 
4.1%
251176
 
4.0%
341147
 
3.9%
321143
 
3.9%
331127
 
3.8%
Other values (46)16731
56.5%
ValueCountFrequency (%)
2164
 
0.2%
22553
 
1.9%
23917
3.1%
241117
3.8%
251176
4.0%
261245
4.2%
271455
4.9%
281397
4.7%
291593
5.4%
301382
4.7%
ValueCountFrequency (%)
791
 
< 0.1%
753
 
< 0.1%
741
 
< 0.1%
734
 
< 0.1%
723
 
< 0.1%
713
 
< 0.1%
7010
< 0.1%
6915
0.1%
685
 
< 0.1%
6716
0.1%

PayStat/Sept05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.01493192798
Minimum-2
Maximum8
Zeros14499
Zeros (%)49.0%
Negative8341
Negative (%)28.2%
Memory size231.4 KiB
2021-07-29T19:05:34.395206image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum8
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.124502894
Coefficient of variation (CV)-75.30862032
Kurtosis2.720747276
Mean-0.01493192798
Median Absolute Deviation (MAD)1
Skewness0.7331730188
Sum-442
Variance1.26450676
MonotonicityNot monotonic
2021-07-29T19:05:34.506937image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
014499
49.0%
-15633
 
19.0%
13662
 
12.4%
-22708
 
9.1%
22640
 
8.9%
3320
 
1.1%
476
 
0.3%
524
 
0.1%
819
 
0.1%
611
 
< 0.1%
ValueCountFrequency (%)
-22708
 
9.1%
-15633
 
19.0%
014499
49.0%
13662
 
12.4%
22640
 
8.9%
3320
 
1.1%
476
 
0.3%
524
 
0.1%
611
 
< 0.1%
79
 
< 0.1%
ValueCountFrequency (%)
819
 
0.1%
79
 
< 0.1%
611
 
< 0.1%
524
 
0.1%
476
 
0.3%
3320
 
1.1%
22640
 
8.9%
13662
 
12.4%
014499
49.0%
-15633
 
19.0%

PayStat/Aug05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.1313131313
Minimum-2
Maximum8
Zeros15476
Zeros (%)52.3%
Negative9712
Negative (%)32.8%
Memory size231.4 KiB
2021-07-29T19:05:34.614033image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum8
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.199642203
Coefficient of variation (CV)-9.135736773
Kurtosis1.557982384
Mean-0.1313131313
Median Absolute Deviation (MAD)0
Skewness0.791420645
Sum-3887
Variance1.439141414
MonotonicityNot monotonic
2021-07-29T19:05:34.728727image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
015476
52.3%
-15990
 
20.2%
23904
 
13.2%
-23722
 
12.6%
3326
 
1.1%
497
 
0.3%
128
 
0.1%
525
 
0.1%
720
 
0.1%
612
 
< 0.1%
ValueCountFrequency (%)
-23722
 
12.6%
-15990
 
20.2%
015476
52.3%
128
 
0.1%
23904
 
13.2%
3326
 
1.1%
497
 
0.3%
525
 
0.1%
612
 
< 0.1%
720
 
0.1%
ValueCountFrequency (%)
81
 
< 0.1%
720
 
0.1%
612
 
< 0.1%
525
 
0.1%
497
 
0.3%
3326
 
1.1%
23904
 
13.2%
128
 
0.1%
015476
52.3%
-15990
 
20.2%

PayStat/Jul05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.1634404243
Minimum-2
Maximum8
Zeros15518
Zeros (%)52.4%
Negative9890
Negative (%)33.4%
Memory size231.4 KiB
2021-07-29T19:05:34.834443image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum8
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.199792708
Coefficient of variation (CV)-7.34085654
Kurtosis2.072829638
Mean-0.1634404243
Median Absolute Deviation (MAD)0
Skewness0.841479725
Sum-4838
Variance1.439502541
MonotonicityNot monotonic
2021-07-29T19:05:34.947146image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
015518
52.4%
-15863
 
19.8%
-24027
 
13.6%
23802
 
12.8%
3237
 
0.8%
476
 
0.3%
727
 
0.1%
623
 
0.1%
521
 
0.1%
14
 
< 0.1%
ValueCountFrequency (%)
-24027
 
13.6%
-15863
 
19.8%
015518
52.4%
14
 
< 0.1%
23802
 
12.8%
3237
 
0.8%
476
 
0.3%
521
 
0.1%
623
 
0.1%
727
 
0.1%
ValueCountFrequency (%)
83
 
< 0.1%
727
 
0.1%
623
 
0.1%
521
 
0.1%
476
 
0.3%
3237
 
0.8%
23802
 
12.8%
14
 
< 0.1%
015518
52.4%
-15863
 
19.8%

PayStat/Jun05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.2183034357
Minimum-2
Maximum8
Zeros16204
Zeros (%)54.7%
Negative9904
Negative (%)33.5%
Memory size231.4 KiB
2021-07-29T19:05:35.058386image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum8
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.172219586
Coefficient of variation (CV)-5.369679968
Kurtosis3.488694804
Mean-0.2183034357
Median Absolute Deviation (MAD)0
Skewness1.003030728
Sum-6462
Variance1.374098757
MonotonicityNot monotonic
2021-07-29T19:05:35.174091image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
016204
54.7%
-15617
 
19.0%
-24287
 
14.5%
23142
 
10.6%
3180
 
0.6%
469
 
0.2%
758
 
0.2%
535
 
0.1%
65
 
< 0.1%
12
 
< 0.1%
ValueCountFrequency (%)
-24287
 
14.5%
-15617
 
19.0%
016204
54.7%
12
 
< 0.1%
23142
 
10.6%
3180
 
0.6%
469
 
0.2%
535
 
0.1%
65
 
< 0.1%
758
 
0.2%
ValueCountFrequency (%)
82
 
< 0.1%
758
 
0.2%
65
 
< 0.1%
535
 
0.1%
469
 
0.2%
3180
 
0.6%
23142
 
10.6%
12
 
< 0.1%
016204
54.7%
-15617
 
19.0%

PayStat/May05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.2639775683
Minimum-2
Maximum8
Zeros16684
Zeros (%)56.4%
Negative9959
Negative (%)33.6%
Memory size231.4 KiB
2021-07-29T19:05:35.282758image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum8
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.136217041
Coefficient of variation (CV)-4.304218152
Kurtosis3.981011416
Mean-0.2639775683
Median Absolute Deviation (MAD)0
Skewness1.013018627
Sum-7814
Variance1.290989165
MonotonicityNot monotonic
2021-07-29T19:05:35.398487image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
016684
56.4%
-15480
 
18.5%
-24479
 
15.1%
22617
 
8.8%
3177
 
0.6%
484
 
0.3%
758
 
0.2%
517
 
0.1%
64
 
< 0.1%
81
 
< 0.1%
ValueCountFrequency (%)
-24479
 
15.1%
-15480
 
18.5%
016684
56.4%
22617
 
8.8%
3177
 
0.6%
484
 
0.3%
517
 
0.1%
64
 
< 0.1%
758
 
0.2%
81
 
< 0.1%
ValueCountFrequency (%)
81
 
< 0.1%
758
 
0.2%
64
 
< 0.1%
517
 
0.1%
484
 
0.3%
3177
 
0.6%
22617
 
8.8%
016684
56.4%
-15480
 
18.5%
-24479
 
15.1%

PayStat/Apr05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.2875578528
Minimum-2
Maximum8
Zeros16053
Zeros (%)54.2%
Negative10480
Negative (%)35.4%
Memory size231.4 KiB
2021-07-29T19:05:35.511149image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum8
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.152205693
Coefficient of variation (CV)-4.006865684
Kurtosis3.428958041
Mean-0.2875578528
Median Absolute Deviation (MAD)0
Skewness0.9528070424
Sum-8512
Variance1.327577958
MonotonicityNot monotonic
2021-07-29T19:05:35.726085image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
016053
54.2%
-15674
 
19.2%
-24806
 
16.2%
22756
 
9.3%
3183
 
0.6%
449
 
0.2%
746
 
0.2%
619
 
0.1%
513
 
< 0.1%
82
 
< 0.1%
ValueCountFrequency (%)
-24806
 
16.2%
-15674
 
19.2%
016053
54.2%
22756
 
9.3%
3183
 
0.6%
449
 
0.2%
513
 
< 0.1%
619
 
0.1%
746
 
0.2%
82
 
< 0.1%
ValueCountFrequency (%)
82
 
< 0.1%
746
 
0.2%
619
 
0.1%
513
 
< 0.1%
449
 
0.2%
3183
 
0.6%
22756
 
9.3%
016053
54.2%
-15674
 
19.2%
-24806
 
16.2%

Outstanding/Sept05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct22441
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50957.43201
Minimum-165580
Maximum964511
Zeros1981
Zeros (%)6.7%
Negative588
Negative (%)2.0%
Memory size231.4 KiB
2021-07-29T19:05:35.871697image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-165580
5-th percentile0
Q13528
median22259
Q366623
95-th percentile200545
Maximum964511
Range1130091
Interquartile range (IQR)63095

Descriptive statistics

Standard deviation73370.2424
Coefficient of variation (CV)1.439833985
Kurtosis9.883084664
Mean50957.43201
Median Absolute Deviation (MAD)21680
Skewness2.673879937
Sum1508390945
Variance5383192470
MonotonicityNot monotonic
2021-07-29T19:05:36.030487image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01981
 
6.7%
390243
 
0.8%
78074
 
0.2%
32670
 
0.2%
31663
 
0.2%
250059
 
0.2%
39649
 
0.2%
240039
 
0.1%
41629
 
0.1%
105025
 
0.1%
Other values (22431)26969
91.1%
ValueCountFrequency (%)
-1655801
< 0.1%
-1549731
< 0.1%
-153081
< 0.1%
-143861
< 0.1%
-115451
< 0.1%
-106821
< 0.1%
-98021
< 0.1%
-90951
< 0.1%
-81871
< 0.1%
-74381
< 0.1%
ValueCountFrequency (%)
9645111
< 0.1%
7468141
< 0.1%
6530621
< 0.1%
6304581
< 0.1%
6217491
< 0.1%
6138601
< 0.1%
6107231
< 0.1%
6085941
< 0.1%
6040191
< 0.1%
5896541
< 0.1%

Outstanding/Aug05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct22069
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48942.18955
Minimum-69777
Maximum983931
Zeros2466
Zeros (%)8.3%
Negative665
Negative (%)2.2%
Memory size231.4 KiB
2021-07-29T19:05:36.193099image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-69777
5-th percentile0
Q12970
median21050
Q363497
95-th percentile194111
Maximum983931
Range1053708
Interquartile range (IQR)60527

Descriptive statistics

Standard deviation70923.98515
Coefficient of variation (CV)1.449137969
Kurtosis10.40862349
Mean48942.18955
Median Absolute Deviation (MAD)20660
Skewness2.71669497
Sum1448737753
Variance5030211670
MonotonicityNot monotonic
2021-07-29T19:05:36.391524image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02466
 
8.3%
390230
 
0.8%
78075
 
0.3%
32674
 
0.2%
31672
 
0.2%
39651
 
0.2%
250051
 
0.2%
240042
 
0.1%
-20029
 
0.1%
41628
 
0.1%
Other values (22059)26483
89.5%
ValueCountFrequency (%)
-697771
< 0.1%
-675261
< 0.1%
-333501
< 0.1%
-300001
< 0.1%
-262141
< 0.1%
-247041
< 0.1%
-247021
< 0.1%
-229601
< 0.1%
-186181
< 0.1%
-180881
< 0.1%
ValueCountFrequency (%)
9839311
< 0.1%
7439701
< 0.1%
6715631
< 0.1%
6467701
< 0.1%
6244751
< 0.1%
6059431
< 0.1%
5977931
< 0.1%
5817751
< 0.1%
5776811
< 0.1%
5728341
< 0.1%

Outstanding/Jul05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct21763
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46803.20327
Minimum-157264
Maximum1664089
Zeros2826
Zeros (%)9.5%
Negative649
Negative (%)2.2%
Memory size231.4 KiB
2021-07-29T19:05:36.599002image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-157264
5-th percentile0
Q12652
median20035
Q359830
95-th percentile186878
Maximum1664089
Range1821353
Interquartile range (IQR)57178

Descriptive statistics

Standard deviation69123.89211
Coefficient of variation (CV)1.476905153
Kurtosis20.14060006
Mean46803.20327
Median Absolute Deviation (MAD)19647
Skewness3.106686615
Sum1385421620
Variance4778112460
MonotonicityNot monotonic
2021-07-29T19:05:36.761383image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02826
 
9.5%
390273
 
0.9%
78072
 
0.2%
31662
 
0.2%
32661
 
0.2%
39647
 
0.2%
250040
 
0.1%
240039
 
0.1%
41629
 
0.1%
20026
 
0.1%
Other values (21753)26126
88.3%
ValueCountFrequency (%)
-1572641
< 0.1%
-615061
< 0.1%
-461271
< 0.1%
-340411
< 0.1%
-254431
< 0.1%
-247021
< 0.1%
-203201
< 0.1%
-177061
< 0.1%
-159101
< 0.1%
-156411
< 0.1%
ValueCountFrequency (%)
16640891
< 0.1%
8550861
< 0.1%
6931311
< 0.1%
6896431
< 0.1%
6896271
< 0.1%
6320411
< 0.1%
5974151
< 0.1%
5789711
< 0.1%
5779571
< 0.1%
5770151
< 0.1%

Outstanding/Jun05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct21303
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43122.5542
Minimum-170000
Maximum891586
Zeros3143
Zeros (%)10.6%
Negative667
Negative (%)2.3%
Memory size231.4 KiB
2021-07-29T19:05:36.929420image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-170000
5-th percentile0
Q12329
median19005
Q354271
95-th percentile174074
Maximum891586
Range1061586
Interquartile range (IQR)51942

Descriptive statistics

Standard deviation64196.38391
Coefficient of variation (CV)1.488696231
Kurtosis11.36854578
Mean43122.5542
Median Absolute Deviation (MAD)18606
Skewness2.82838955
Sum1276470727
Variance4121175708
MonotonicityNot monotonic
2021-07-29T19:05:37.094050image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
03143
 
10.6%
390245
 
0.8%
78099
 
0.3%
31668
 
0.2%
32661
 
0.2%
39643
 
0.1%
240039
 
0.1%
15039
 
0.1%
250034
 
0.1%
41633
 
0.1%
Other values (21293)25797
87.1%
ValueCountFrequency (%)
-1700001
< 0.1%
-813341
< 0.1%
-651671
< 0.1%
-506161
< 0.1%
-466271
< 0.1%
-345031
< 0.1%
-274901
< 0.1%
-243031
< 0.1%
-221081
< 0.1%
-203201
< 0.1%
ValueCountFrequency (%)
8915861
< 0.1%
7068641
< 0.1%
6286991
< 0.1%
6168361
< 0.1%
5728051
< 0.1%
5690341
< 0.1%
5656691
< 0.1%
5635431
< 0.1%
5480201
< 0.1%
5426531
< 0.1%

Outstanding/May05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct20783
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40235.54518
Minimum-81334
Maximum927171
Zeros3433
Zeros (%)11.6%
Negative649
Negative (%)2.2%
Memory size231.4 KiB
2021-07-29T19:05:37.256118image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-81334
5-th percentile0
Q11780
median18091
Q350072
95-th percentile165725
Maximum927171
Range1008505
Interquartile range (IQR)48292

Descriptive statistics

Standard deviation60699.34488
Coefficient of variation (CV)1.508600035
Kurtosis12.35959093
Mean40235.54518
Median Absolute Deviation (MAD)17673
Skewness2.880165904
Sum1191012373
Variance3684410469
MonotonicityNot monotonic
2021-07-29T19:05:37.413692image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
03433
 
11.6%
390234
 
0.8%
78091
 
0.3%
31679
 
0.3%
32661
 
0.2%
15058
 
0.2%
39645
 
0.2%
240039
 
0.1%
250037
 
0.1%
41636
 
0.1%
Other values (20773)25488
86.1%
ValueCountFrequency (%)
-813341
< 0.1%
-613721
< 0.1%
-530071
< 0.1%
-466271
< 0.1%
-375941
< 0.1%
-361561
< 0.1%
-304811
< 0.1%
-283351
< 0.1%
-230031
< 0.1%
-207531
< 0.1%
ValueCountFrequency (%)
9271711
< 0.1%
8235401
< 0.1%
5870671
< 0.1%
5517021
< 0.1%
5478801
< 0.1%
5306721
< 0.1%
5243151
< 0.1%
5161391
< 0.1%
5141141
< 0.1%
5082131
< 0.1%

Outstanding/Apr05
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct20396
Distinct (%)68.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38858.44982
Minimum-339603
Maximum961664
Zeros3929
Zeros (%)13.3%
Negative679
Negative (%)2.3%
Memory size231.4 KiB
2021-07-29T19:05:37.563298image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-339603
5-th percentile0
Q11278
median17118
Q349121
95-th percentile161912
Maximum961664
Range1301267
Interquartile range (IQR)47843

Descriptive statistics

Standard deviation59519.89304
Coefficient of variation (CV)1.531710434
Kurtosis12.3451577
Mean38858.44982
Median Absolute Deviation (MAD)16793
Skewness2.852904777
Sum1150248973
Variance3542617668
MonotonicityNot monotonic
2021-07-29T19:05:37.740784image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
03929
 
13.3%
390204
 
0.7%
78086
 
0.3%
15077
 
0.3%
31677
 
0.3%
32654
 
0.2%
39645
 
0.2%
41636
 
0.1%
-1833
 
0.1%
240032
 
0.1%
Other values (20386)25028
84.6%
ValueCountFrequency (%)
-3396031
< 0.1%
-2090511
< 0.1%
-1509531
< 0.1%
-946251
< 0.1%
-738951
< 0.1%
-570601
< 0.1%
-514431
< 0.1%
-511831
< 0.1%
-466271
< 0.1%
-457341
< 0.1%
ValueCountFrequency (%)
9616641
< 0.1%
6999441
< 0.1%
5686381
< 0.1%
5277111
< 0.1%
5275661
< 0.1%
5149751
< 0.1%
5137981
< 0.1%
5119051
< 0.1%
5013701
< 0.1%
4991001
< 0.1%

Paid/Sept05
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct7862
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5649.560319
Minimum0
Maximum873552
Zeros5192
Zeros (%)17.5%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:37.914320image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11000
median2100
Q35005
95-th percentile18393
Maximum873552
Range873552
Interquartile range (IQR)4005

Descriptive statistics

Standard deviation16568.26494
Coefficient of variation (CV)2.932664492
Kurtosis419.7892648
Mean5649.560319
Median Absolute Deviation (MAD)1931
Skewness14.77258405
Sum167232635
Variance274507403.2
MonotonicityNot monotonic
2021-07-29T19:05:38.064508image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
05192
 
17.5%
20001340
 
4.5%
3000880
 
3.0%
5000689
 
2.3%
1500501
 
1.7%
4000416
 
1.4%
10000396
 
1.3%
1000360
 
1.2%
2500297
 
1.0%
6000291
 
1.0%
Other values (7852)19239
65.0%
ValueCountFrequency (%)
05192
17.5%
19
 
< 0.1%
214
 
< 0.1%
315
 
0.1%
417
 
0.1%
512
 
< 0.1%
615
 
0.1%
79
 
< 0.1%
88
 
< 0.1%
97
 
< 0.1%
ValueCountFrequency (%)
8735521
< 0.1%
5050001
< 0.1%
4933581
< 0.1%
4239031
< 0.1%
4050161
< 0.1%
3681991
< 0.1%
3230141
< 0.1%
3048151
< 0.1%
3020001
< 0.1%
3000391
< 0.1%

Paid/Aug05
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct7814
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5894.788386
Minimum0
Maximum1684259
Zeros5334
Zeros (%)18.0%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:38.215065image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1825
median2007
Q35000
95-th percentile18934
Maximum1684259
Range1684259
Interquartile range (IQR)4175

Descriptive statistics

Standard deviation23089.19362
Coefficient of variation (CV)3.916882526
Kurtosis1649.750282
Mean5894.788386
Median Absolute Deviation (MAD)1993
Skewness30.62926199
Sum174491631
Variance533110862.1
MonotonicityNot monotonic
2021-07-29T19:05:38.374640image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
05334
 
18.0%
20001274
 
4.3%
3000848
 
2.9%
5000707
 
2.4%
1000585
 
2.0%
1500516
 
1.7%
4000402
 
1.4%
10000313
 
1.1%
6000281
 
0.9%
2500249
 
0.8%
Other values (7804)19092
64.5%
ValueCountFrequency (%)
05334
18.0%
115
 
0.1%
220
 
0.1%
318
 
0.1%
411
 
< 0.1%
525
 
0.1%
68
 
< 0.1%
712
 
< 0.1%
89
 
< 0.1%
96
 
< 0.1%
ValueCountFrequency (%)
16842591
< 0.1%
12270821
< 0.1%
12154711
< 0.1%
10245161
< 0.1%
5804641
< 0.1%
4155521
< 0.1%
4010031
< 0.1%
3881261
< 0.1%
3852281
< 0.1%
3849861
< 0.1%

Paid/Jul05
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct7431
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5198.415898
Minimum0
Maximum896040
Zeros5891
Zeros (%)19.9%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:38.543929image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1390
median1800
Q34500
95-th percentile17337
Maximum896040
Range896040
Interquartile range (IQR)4110

Descriptive statistics

Standard deviation17580.91481
Coefficient of variation (CV)3.381975423
Kurtosis574.5439067
Mean5198.415898
Median Absolute Deviation (MAD)1793
Skewness17.41906579
Sum153878309
Variance309088565.4
MonotonicityNot monotonic
2021-07-29T19:05:38.692490image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
05891
 
19.9%
20001267
 
4.3%
10001092
 
3.7%
3000862
 
2.9%
5000710
 
2.4%
1500484
 
1.6%
4000375
 
1.3%
10000312
 
1.1%
1200241
 
0.8%
6000238
 
0.8%
Other values (7421)18129
61.2%
ValueCountFrequency (%)
05891
19.9%
113
 
< 0.1%
219
 
0.1%
314
 
< 0.1%
415
 
0.1%
517
 
0.1%
614
 
< 0.1%
718
 
0.1%
810
 
< 0.1%
911
 
< 0.1%
ValueCountFrequency (%)
8960401
< 0.1%
8890431
< 0.1%
5082291
< 0.1%
4175881
< 0.1%
4009721
< 0.1%
3970921
< 0.1%
3804781
< 0.1%
3717181
< 0.1%
3493951
< 0.1%
3442611
< 0.1%

Paid/Jun05
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct6880
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4828.659268
Minimum0
Maximum621000
Zeros6318
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:38.844084image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1298
median1500
Q34014
95-th percentile16014
Maximum621000
Range621000
Interquartile range (IQR)3716

Descriptive statistics

Standard deviation15711.05799
Coefficient of variation (CV)3.253710216
Kurtosis277.6714652
Mean4828.659268
Median Absolute Deviation (MAD)1500
Skewness12.93192018
Sum142933143
Variance246837343.2
MonotonicityNot monotonic
2021-07-29T19:05:38.993683image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
06318
 
21.3%
10001381
 
4.7%
20001197
 
4.0%
3000876
 
3.0%
5000805
 
2.7%
1500437
 
1.5%
4000393
 
1.3%
10000336
 
1.1%
2500255
 
0.9%
500253
 
0.9%
Other values (6870)17350
58.6%
ValueCountFrequency (%)
06318
21.3%
121
 
0.1%
222
 
0.1%
313
 
< 0.1%
420
 
0.1%
512
 
< 0.1%
616
 
0.1%
711
 
< 0.1%
87
 
< 0.1%
99
 
< 0.1%
ValueCountFrequency (%)
6210001
< 0.1%
5288971
< 0.1%
4970001
< 0.1%
4321301
< 0.1%
4000461
< 0.1%
3317881
< 0.1%
3309821
< 0.1%
3200081
< 0.1%
3130941
< 0.1%
2929621
< 0.1%

Paid/May05
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct6837
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4795.032735
Minimum0
Maximum426529
Zeros6600
Zeros (%)22.3%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:39.153296image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1259
median1500
Q34042
95-th percentile16002
Maximum426529
Range426529
Interquartile range (IQR)3783

Descriptive statistics

Standard deviation15244.21715
Coefficient of variation (CV)3.179168526
Kurtosis182.477426
Mean4795.032735
Median Absolute Deviation (MAD)1500
Skewness11.19205537
Sum141937764
Variance232386156.6
MonotonicityNot monotonic
2021-07-29T19:05:39.300904image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
06600
 
22.3%
10001323
 
4.5%
20001302
 
4.4%
3000940
 
3.2%
5000804
 
2.7%
1500419
 
1.4%
4000398
 
1.3%
10000340
 
1.1%
500245
 
0.8%
6000243
 
0.8%
Other values (6827)16987
57.4%
ValueCountFrequency (%)
06600
22.3%
121
 
0.1%
212
 
< 0.1%
313
 
< 0.1%
412
 
< 0.1%
58
 
< 0.1%
67
 
< 0.1%
79
 
< 0.1%
86
 
< 0.1%
96
 
< 0.1%
ValueCountFrequency (%)
4265291
< 0.1%
4179901
< 0.1%
3880711
< 0.1%
3792671
< 0.1%
3320001
< 0.1%
3317881
< 0.1%
3309821
< 0.1%
3268891
< 0.1%
3170771
< 0.1%
3101351
< 0.1%

Paid/Apr05
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct6884
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5181.326374
Minimum0
Maximum528666
Zeros7043
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size231.4 KiB
2021-07-29T19:05:39.448467image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1138
median1500
Q34000
95-th percentile17324
Maximum528666
Range528666
Interquartile range (IQR)3862

Descriptive statistics

Standard deviation17657.26074
Coefficient of variation (CV)3.407864987
Kurtosis172.8169309
Mean5181.326374
Median Absolute Deviation (MAD)1500
Skewness10.81967246
Sum153372442
Variance311778856.8
MonotonicityNot monotonic
2021-07-29T19:05:39.608081image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
07043
23.8%
10001290
 
4.4%
20001279
 
4.3%
3000907
 
3.1%
5000797
 
2.7%
1500434
 
1.5%
4000404
 
1.4%
10000355
 
1.2%
500246
 
0.8%
6000214
 
0.7%
Other values (6874)16632
56.2%
ValueCountFrequency (%)
07043
23.8%
120
 
0.1%
29
 
< 0.1%
314
 
< 0.1%
412
 
< 0.1%
56
 
< 0.1%
66
 
< 0.1%
75
 
< 0.1%
86
 
< 0.1%
97
 
< 0.1%
ValueCountFrequency (%)
5286661
< 0.1%
5271431
< 0.1%
4430011
< 0.1%
4220001
< 0.1%
4035001
< 0.1%
3770001
< 0.1%
3724951
< 0.1%
3512821
< 0.1%
3452931
< 0.1%
3080001
< 0.1%

Default
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.0 KiB
False
22996 
True
6605 
ValueCountFrequency (%)
False22996
77.7%
True6605
 
22.3%
2021-07-29T19:05:39.708819image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

PayStats
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct47
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.92047566
Minimum-6
Maximum42
Zeros2470
Zeros (%)8.3%
Negative4405
Negative (%)14.9%
Memory size231.4 KiB
2021-07-29T19:05:39.805520image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-6
5-th percentile-6
Q11
median6
Q36
95-th percentile16
Maximum42
Range48
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.905153497
Coefficient of variation (CV)1.200118425
Kurtosis2.683194013
Mean4.92047566
Median Absolute Deviation (MAD)3
Skewness0.6948094664
Sum145651
Variance34.87083783
MonotonicityNot monotonic
2021-07-29T19:05:39.954949image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
610023
33.9%
02470
 
8.3%
-62072
 
7.0%
81864
 
6.3%
51321
 
4.5%
21148
 
3.9%
41056
 
3.6%
31046
 
3.5%
11045
 
3.5%
-3859
 
2.9%
Other values (37)6697
22.6%
ValueCountFrequency (%)
-62072
7.0%
-587
 
0.3%
-4291
 
1.0%
-3859
 
2.9%
-2481
 
1.6%
-1615
 
2.1%
02470
8.3%
11045
3.5%
21148
3.9%
31046
3.5%
ValueCountFrequency (%)
421
 
< 0.1%
3919
0.1%
3820
0.1%
379
 
< 0.1%
361
 
< 0.1%
351
 
< 0.1%
3427
0.1%
3312
< 0.1%
321
 
< 0.1%
313
 
< 0.1%

Interactions

2021-07-29T19:04:16.400431image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:16.544082image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:16.690694image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:16.840277image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:16.988878image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:17.144045image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:17.286625image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:17.433873image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:17.581515image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:17.718151image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:17.935531image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:18.106073image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:18.251725image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:18.397297image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:18.530981image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:18.675552image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:18.817179image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:18.963275image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:19.101213image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:19.242843image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:19.374003image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:19.509682image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:19.649268image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:19.796873image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:19.946511image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:20.086138image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:20.335190image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:20.474292image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:20.612960image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:20.772537image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:20.913098image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:21.052606image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:21.194185image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:21.335845image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:21.485446image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:21.633051image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:21.774670image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:21.925229image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:22.061865image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:22.208967image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:22.343602image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:22.484044image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:22.614940image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:22.753042image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:22.899690image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:23.050246image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:23.192906image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:23.337477image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:23.493061image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:23.632304image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:23.776114image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:23.916059image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:24.053695image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:24.192326image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:24.335661image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:24.470303image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:24.615954image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:24.761535image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:25.024858image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:25.175452image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:25.317037image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:25.458133image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:25.593818image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:25.733180image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:25.866827image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:26.011436image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:26.140138image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:26.279717image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:26.409371image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:26.541060image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:26.668719image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:26.799329image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:26.926072image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:27.066694image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:27.215857image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:27.360664image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:27.499332image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:27.636925image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:27.792547image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:27.951126image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:28.092745image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:28.240350image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:28.385979image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:28.540676image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:28.670329image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:28.812674image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:28.956340image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:29.094969image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:29.232644image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:29.379210image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:29.511853image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:29.656467image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:29.789112image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:29.941805image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:30.080029image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:30.224619image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:30.358285image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:30.491440image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:30.782702image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:30.921293image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:31.074921image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:31.214508image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:31.354174image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:31.495264image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:31.629906image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:31.769362image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:31.903850image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:32.048031image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:32.187132image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:32.324799image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:32.456410image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:32.593086image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:32.726700image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:32.865318image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:32.994970image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:33.131605image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:33.261693image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:33.395342image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:33.523729image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:33.655497image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:33.795163image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:33.936783image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:34.080439image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:34.214044image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:34.348684image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:34.488348image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:34.619002image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:34.761090image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:34.889226image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:35.029892image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:35.161498image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:35.299177image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:35.425797image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:35.561436image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:35.697074image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:35.835702image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:35.973335image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:36.101037image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:36.232639image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:36.362375image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:36.494987image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:36.621196image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:36.759768image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:36.894408image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:37.036068image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:37.169714image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:37.298367image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:37.650371image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:37.801273image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:37.958927image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:38.097556image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:38.301569image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:38.470277image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:38.611261image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:38.749852image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:38.902005image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:39.048128image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:39.188751image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:39.336395image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:39.474985image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:39.618277image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:39.748936image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:39.880653image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:40.020319image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:40.173229image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:40.329381image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:40.491132image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:40.630756image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:40.768349image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:40.928431image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:41.088012image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:41.234620image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:41.393707image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:41.549338image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:41.675999image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:41.851328image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:42.062027image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:42.216526image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:42.364029image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:42.520216image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:42.669227image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:42.833935image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:43.011300image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:43.211424image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:43.379208image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:43.534345image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:43.706438image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:43.867131image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:44.024247image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:44.166384image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:44.307008image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:44.448262image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:44.577944image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:44.742898image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:44.889574image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:45.048316image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:45.184474image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:45.323595image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:45.471237image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:45.649725image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:45.852143image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:46.051653image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:46.245476image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:46.415109image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:46.599332image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:46.772963image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:46.932059image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:47.292694image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:47.454293image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:47.602068image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:47.753552image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:47.917077image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:48.147033image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:48.345241image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:48.542022image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:48.739532image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:48.912101image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:49.093118image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:49.258344image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:49.405994image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:49.552345image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:49.744344image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:49.920234image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:50.096358image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:50.296836image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:50.499335image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:50.692894image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:50.847991image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:51.003528image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:51.150056image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:51.328261image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:51.531848image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:51.735874image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:51.953140image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:52.127025image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:52.319147image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:52.471162image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:52.620855image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:52.758527image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:52.969953image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:53.146875image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:53.324030image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:53.508176image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:53.708199image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:53.901066image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:54.078245image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:54.235071image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:54.391735image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:54.547809image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:54.699870image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:54.855011image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:55.017532image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:55.178120image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:55.330740image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:55.492308image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:55.662723image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:55.821410image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:55.978945image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:56.124145image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:56.284297image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:56.426272image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:56.591391image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:56.815302image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:57.029271image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:57.210034image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:57.432124image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:57.615196image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:57.817239image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:58.018563image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:58.187418image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:58.361983image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:58.537071image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:58.710265image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:58.867228image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:59.036284image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:59.199514image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:59.388661image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:59.552673image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:04:59.714483image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:00.220058image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:00.382101image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:00.553281image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:00.709025image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:00.874026image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:01.025526image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:01.186104image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:01.338208image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:01.492373image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:01.650489image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:01.810298image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:01.964454image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:02.125125image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:02.296352image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:02.451390image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:02.604244image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:02.761092image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:02.926253image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:03.092806image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:03.257159image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:03.420235image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:03.568450image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:03.731024image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:03.882156image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:04.054713image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:04.203451image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:04.368951image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:04.524129image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:04.681533image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:04.828153image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:05.000314image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:05.176400image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:05.353757image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:05.538337image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:05.699771image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:05.880054image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:06.049448image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:06.221645image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:06.392723image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:06.572575image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:06.752365image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:06.936454image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:07.103161image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:07.255268image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:07.408894image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:07.553140image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:07.714794image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:07.863429image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:08.031977image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:08.186561image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:08.360439image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:08.504342image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:08.642508image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:08.774191image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:08.903850image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:09.036048image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:09.169228image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:09.306826image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:09.442531image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:09.576702image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:09.711273image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:09.857884image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:09.995515image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:10.139131image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:10.276733image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:10.406374image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:10.561001image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:10.699589image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:10.843515image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:10.967145image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:11.103265image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:11.228952image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:11.359571image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:11.483227image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:11.629875image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:11.774484image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:11.923052image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:12.064715image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:12.207878image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:12.355051image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:12.497654image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:12.642278image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:12.782131image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:12.938709image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:13.155093image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:13.347452image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:13.528991image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:13.725078image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:13.912237image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:14.081202image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:14.601129image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:14.756942image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:14.911530image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:15.051958image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:15.205014image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:15.343221image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:15.485802image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:15.622482image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:15.762081image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:15.909687image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:16.046339image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:16.180019image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:16.314315image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:16.450949image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:16.589582image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:16.727189image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:16.863853image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:17.012451image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:17.147053image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:17.282690image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:17.430293image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:17.558991image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:17.708145image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:17.835806image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:17.982213image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:18.116298image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:18.256882image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:18.391077image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:18.536654image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:18.739189image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:18.888610image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:19.029776image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:19.179380image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:19.326946image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:19.481257image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:19.619886image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:19.765916image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:19.913241image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:20.068253image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:20.225432image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:20.386317image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:20.534909image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:20.679522image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:20.816156image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:20.958814image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:21.111370image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:21.267985image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:21.406173image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:21.547793image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:21.691337image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:21.829083image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:21.967749image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:22.101355image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:22.242010image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:22.378616image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:22.506273image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:22.632972image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:22.761589image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:22.893827image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:23.032053image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:23.161316image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:23.313853image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:23.463496image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:23.593579image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:23.730722image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:23.855433image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:23.997050image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:24.119681image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:24.255318image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:24.382019image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:24.515137image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:24.641800image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:24.783468image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:24.920349image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:25.050158image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:25.187377image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:25.319572image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:25.451222image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:25.584824image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:25.723452image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:25.855100image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:25.996723image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:26.132360image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:26.276978image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:26.414670image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:26.548208image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:26.690147image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:26.827808image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:26.969982image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:27.098123image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:27.240744image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:27.453180image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:27.587816image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:27.717468image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:27.849155image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:27.982798image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:28.109419image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:28.238076image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:28.363781image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:28.484981image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:28.611207image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:28.739821image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:28.869514image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:29.001119image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:29.134763image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:29.274390image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:29.411065image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:29.540271image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:29.677904image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:29.802640image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:29.941264image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:30.065167image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:30.585317image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:30.708990image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T19:05:30.835611image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Correlations

2021-07-29T19:05:40.128532image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-07-29T19:05:40.471572image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-07-29T19:05:40.810668image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-07-29T19:05:41.157739image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-07-29T19:05:41.460186image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-07-29T19:05:31.145779image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-07-29T19:05:32.118524image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

Unnamed: 0Credit LimitSexEducationMarital StatusAgePayStat/Sept05PayStat/Aug05PayStat/Jul05PayStat/Jun05PayStat/May05PayStat/Apr05Outstanding/Sept05Outstanding/Aug05Outstanding/Jul05Outstanding/Jun05Outstanding/May05Outstanding/Apr05Paid/Sept05Paid/Aug05Paid/Jul05Paid/Jun05Paid/May05Paid/Apr05DefaultPayStats
0120000FBScMarried2422-1-1-2-23913310268900006890000True4
12120000FBScSingle26-120002268217252682327234553261010001000100002000True9
2390000FBScSingle34000000292391402713559143311494815549151815001000100010005000False6
3450000FBScMarried37000000469904823349291283142895929547200020191200110010691000False6
4550000MBScMarried57-10-10008617567035835209401914619131200036681100009000689679False4
5650000MMSc or PHdSingle370000006440057069576081939419619200242500181565710001000800False6
67500000MMSc or PHdSingle29000000367965412023445007542653483003473944550004000038000202391375013770False6
78100000FBScSingle230-1-100-111876380601221-159567380601058116871542False3
89140000FHigh School DiplomaMarried280020001128514096121081221111793371933290432100010001000False8
91020000MHigh School DiplomaSingle35-2-2-2-2-1-1000013007139120001300711220False-4

Last rows

Unnamed: 0Credit LimitSexEducationMarital StatusAgePayStat/Sept05PayStat/Aug05PayStat/Jul05PayStat/Jun05PayStat/May05PayStat/Apr05Outstanding/Sept05Outstanding/Aug05Outstanding/Jul05Outstanding/Jun05Outstanding/May05Outstanding/Apr05Paid/Sept05Paid/Aug05Paid/Jul05Paid/Jun05Paid/May05Paid/Apr05DefaultPayStats
2959129991140000MBScMarried410000001383251371421391101382624967546121600070004228150520002000False6
2959229992210000MBScMarried34322222250025002500250025002500000000True19
295932999310000MHigh School DiplomaMarried43000-2-2-28802104000000200000000False0
2959429994100000MMSc or PHdSingle380-1-10003042142710299670626694735500420001117844000300020002000False4
295952999580000MBScSingle34222222725577770879384775198260781158700035000700004000True18
2959629996220000MHigh School DiplomaMarried390000001889481928152083658800431237159808500200005003304750001000False6
2959729997150000MHigh School DiplomaSingle43-1-1-1-10016831828350289795190018373526899812900False2
295982999830000MBScSingle37432-1003565335627582087820582193570022000420020003100True14
295992999980000MHigh School DiplomaMarried411-1000-1-1645783797630452774118554894485900340911781926529641804True5
296003000050000MBScMarried46000000479294890549764365353242815313207818001430100010001000True6